Mining association rules procedure to support on-line recommendation by customers and products fragmentation

Changchien, Shih-Kuen; Lu, Tzu-Chuen

doi:10.1016/s0957-4174(01)00017-3

Cited by 123 publications

(45 citation statements)

References 22 publications

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“…Association rule mining is widely used for analyzing the product items purchased by consumers. It is also used to support sales promotion and marketing segmentation [7][8]. The association rule is represented by XÎY where X and Y are a set of items.…”

Section: Association Rule Miningmentioning

confidence: 99%

Customized products and cloud service information system development research

Hung

2017

MATEC Web Conf.

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Abstract. This study presents a cloud service customized product information system to enable businesses to provide customized product marketing on the Internet to meet consumer demand for customized products. The cloud service of the information system development strategic framework proposed in this study contains three elements: (1) e-commerce services, (2) promotion type modules, and (3) cloud services customized promotional products. In this study, a mining cloud information system to detect customer behavior is proposed. The association rules from relational database design are utilized to mine consumer behavior to generate crossselling proposals for customer products and marketing for a retailing mall in Taiwan. The study is composed of several parts, as follows. A market segment and application of association rules in data exploration techniques (Association Rule Mining) and sequence-like exploration (Sequential Pattern Mining), efficient analysis of customers, consumer behavior, identification of candidates for promotional products, and using cloud service delivery and evaluation of targets to evaluate candidates for promotional products for production. However, in addition to cloud service customized promotional products, the quantity of promotional products sales varies for different customers. We strive to achieve increased customer loyalty and profits through the use of active cloud service customized promotional products.

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Section: Association Rule Miningmentioning

confidence: 99%

Customized products and cloud service information system development research

Hung

2017

MATEC Web Conf.

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“…All Among the various data mining techniques, association rules mining [22] is popular in marketing intelligence fields. However, association rule mining is applied to the task of web mining.…”

Section: Association Rules Miningmentioning

confidence: 99%

Web Log based Analysis of User's Browsing Behavior

Ladekar¹,

Pawar²,

Raikar³

et al. 2015

IJCA

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In The increasing craze of internet has geared a number of modern firms for using web technology in their day to day lives. A remarkable ability to analyze web log data is provided to them by the web mining technology, that are putatively full of information, but frequently lacking with meaningful information. This signifies the need to the development of an inference mechanism which is advanced and that draws out richer implication from mining's output. This paper presents a web mining algorithm that aims at amending the interpretations of the draft's output of association rule mining. This algorithm is being tremendously used in web mining. The results obtained prove robustness of the algorithm proposed in this paper.

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“…A large number of studies use association rules analysis in a wide variety of areas: biology (Becquet, Blachon, Jeudy, Boulicaut & Gandrillon, 2002;Marghny & El-Semman, 2005), business and marketing (Changchien & Lu, 2001), geography (Appice, Ceci, Lanza, Lisi & Malerba, 2003;Ding, Ding & Perrizo, 2002;Lee, Hong, Ko, Tsao & Lin, 2007), agriculture (Matsumoto, 1998), education (Garcia, Romero, Ventura & Calders, 2007;Garcia, Amandi, Schiaffino & Campo, 2007), photography (Liu, Weng, Tseng, Chuang & Chen, 2008), economics (Dopfer & Potts, 2004;Kuo, Lin & Shih, 2007), and so on.…”

Section: Poisson Regression and Association Rules Analysismentioning

confidence: 99%

Model Selection for Poisson Regression via Association Rules Analysis

Changpetch¹,

Lin²

2015

IJSP

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This study integrates association rules analysis, a methodology for selecting potential interactions, with Poisson regression modeling. Though typically ignored in conventional Poisson regression, interactions are very common in practice. However, selecting a Poisson regression model when many main effects and interactions are involved is problematic. In this study, we develop a model selection framework to address this problem. Specifically, we focus on building an optimal Poisson regression model by (1) discretizing the response and quantitative attributes into levels; (2) exploring via association rules analysis combinations of input variables that have a significant impact on response; (3) selecting potential (low-and high-order) interactions; (4) converting these potential interactions into new variables; and (5) selecting variables from all the input variables and the newly created variables (interactions) to build the optimal Poisson regression model. Our model selection procedure is the first approach to enable a global search for potential interactions and the first to establish the optimal combination of main effects and interaction effects in the Poisson regression model. A real-life example is given for illustration. It is shown that the proposed method finds the optimal model including important interactions that cannot be found by other existing methods.

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Mining association rules procedure to support on-line recommendation by customers and products fragmentation

Cited by 123 publications

References 22 publications

Customized products and cloud service information system development research

Customized products and cloud service information system development research

Web Log based Analysis of User's Browsing Behavior

Model Selection for Poisson Regression via Association Rules Analysis

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Mining association rules procedure to support on-line recommendation by customers and products fragmentation

Cited by 123 publications

References 22 publications

Customized products and cloud service information system development research

Customized products and cloud service information system development research

Web Log based Analysis of User&apos;s Browsing Behavior

Model Selection for Poisson Regression via Association Rules Analysis

Contact Info

Product

Resources

About

Web Log based Analysis of User's Browsing Behavior